Instructions to use amburger66/robometer-4b-lora-robotsmith-task02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amburger66/robometer-4b-lora-robotsmith-task02 with Transformers:
# Load model directly from transformers import AutoProcessor, RBM processor = AutoProcessor.from_pretrained("amburger66/robometer-4b-lora-robotsmith-task02") model = RBM.from_pretrained("amburger66/robometer-4b-lora-robotsmith-task02") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
base_model: Qwen/Qwen3-VL-4B-Instruct
tags:
- reward_model
- rbm
- preference_comparisons
library_name: transformers
amburger66/robometer-4b-lora-robotsmith-task02
Model Details
- Base Model: Qwen/Qwen3-VL-4B-Instruct
- Model Type: qwen3_vl
Training Run
- Wandb Run: lora_task02
- Wandb ID:
k51jvvii - Project: rbm-finetune-robotsmith
- Notes: fine-tuning Robometer on RobotSmith
Citation
If you use this model, please cite: